Xianzhi Wang

School of Computer Science at University of Technology Sydney, Sydney, Australia

Research profile (Orcid, Google Scholar, Scopus authors, others):

ORCID: 0000-0001-9582-3445

Scopus ID: https://www.scopus.com/authid/detail.uri?authorId=36189130500

ResearchGate: https://www.researchgate.net/profile/Xianzhi-Wang-7

Google Scholar: https://scholar.google.com/citations?user=Xej6piMAAAAJ&hl=en.

BIO

Dr. Xianzhi Wang is a Senior Lecturer in the School of Computer Science, Faculty of Engineering and IT,  University of Technology Sydney.

Xianzhi's research interests include Internet of Things (IoT), data mining, machine learning, and recommender systems. His publications appear in top-tier journals (e.g., IEEE TNNLS, IEEE MC, IEEE TSC, ACM TIST, ACM TOIT) and top conferences (e.g., ICDM, KDD, WSDM, AAAI, IJCAI, ICDE, UbiComp, SIGIR, CIKM).

He actively serves as a PC member for premier conferences (e.g., WSDM, KDD, SIGIR, NeurIPS, ACL, IJCAI, AAAI, TheWebConf, and SDM) and regularly reviews for IEEE TAI, TBD, TII, TITS, TEM, TCSS, TCB, and TKDE. He is the recipient of ARC DECRA, DP, LP and LIEF grants, two Best Paper Awards (IEEE SCC, CCF NCSC), and IBM PhD Fellowship. He served as an Area Chair for ACL'23, ADMA'23, FiCloud'22, ICSOC'22 and Guest Editor for ACM TIST, ACM TOSN, and Springer PRL. He is on the Editorial Board of six international journals and holds various chairing roles in five other conferences. Xianzhi is passionate about applying smart sensing, machine learning, data mining, and recommendation techniques to real-world applications.

DEGREES

PhD

Harbin Institute of Technology, Harbin, China

LANGUAGES

English

Can read, write, speak, understand and peer review

Chinese (Mandarin)

Can read, write, speak, understand and peer review

UN SUSTAINABLE DEVELOPMENT GOALS

9 Industry, Innovation and Infrastructure

11 Sustainable Cities and Communities

13 Climate Action

10 Reduced Inequalities

AVAILABILITY

Masters Research or PhD student supervision

Industry Projects

Collaborative projects

DISCIPLINES

Data management and data science

Machine learning

Artificial intelligence